Sharif Digital Repository

This paper presents a comprehensive operation model for micro-grids (MG) operating in the islanded mode. Various energy sources of a MG including diesel engine generator, micro-turbine, wind turbine and photovoltaic cell as well as battery storage and AC/DC rectifier/inverter are modeled in the proposed framework. Fuel costs, emission costs, and operation and maintenance (O&M) costs of these sources as well as their operating limits and characteristics are considered in the model. Furthermore, a new multi-cross learning-based chaotic differential evolution (MLCDE) algorithm is presented to solve the optimization problem of MG operation. The numerical results obtained from the proposed... 

A repeated inflation-unemployment game within the linear-quadratic frame-work of Barro and Gordon is studied assuming that the government would like to cheat optimally and the finite heterogeneous population of private agents attempts to learn the government's targets using a reinforcement learning algorithm. Private agents are heterogeneous in their initial expectations of inflation rate but are assumed to utilize an identical anticipatory reinforcement learning process, namely Q-learning. In our heterogeneous setting, the only way for the private agents to achieve a zero value for their loss function, is for all of them to correctly anticipate the Nash equilibrium. It is of particular... 

A repeated inflation-unemployment game within the linear-quadratic framework of Barro and Gordon is studied assuming that the government would like to cheat optimally and the finite heterogeneous population of private agents attempts to learn the government's targets using a reinforcement learning algorithm. Private agents are heterogeneous in their initial expectations of inflation rate but are assumed to utilize an identical anticipatory reinforcement learning process, namely Q-learning. In our heterogeneous setting, the only way for the private agents to achieve a zero value for their loss function, is for all of them to correctly anticipate the Nash equilibrium. It is of particular... 

This paper deals with the problem of multi-agent learning of a population of players, engaged in a repeated normal-form game. Assuming boundedly-rational agents, we propose a model of social learning based on trial and error, called "social reinforcement learning". This extension of well-known Q-learning algorithm, allows players within a population to communicate and share their experiences with each other. To illustrate the effectiveness of the proposed learning algorithm, a number of simulations on the benchmark game of "Battle of Sexes" has been carried out. Results show that supplementing communication to the classical form of Q-learning, significantly improves convergence speed towards... 

In the recent years, declination of oil reservoir causes the importance of researches on enhancement of oil recovery processes become more important. One of wide applicable approaches in enhancement of oil recovery is carbon dioxide injection which becomes interested because of relative low cost, good displacement and environmentally aspects. The injection of carbon dioxide to oil reservoir causes the lighter hydrocarbons of crude oil are extracted by CO2. This phenomena can be affected by various factors such the solubility of hydrocarbons in carbon dioxide so in the present investigation Fuzzy c-means (FCM) as a novel approach for estimation of solubility of alkanes in carbon dioxide in... 

Gasification of biomass in supercritical water is a successful technology for hydrogen production especially by using wet biomass. The whole process, from feeding to purification of hydrogen, consists of a lot of equipment, such as pumps, heat exchangers, heaters, reactors, etc. Because the main reactions take place in the gasification reactor, the gasifier is the most important equipment of the process. In this article, a thermodynamic model, including chemical equilibrium in the reactor that is based on Gibbs free energy minimization, is developed to estimate equilibrium composition for gasification of biomass in supercritical water for hydrogen production. For this analysis, we use three... 

Compared with fossil fuel, biomass is a clean energy with zero CO 2 emission, because CO 2 is fixed by photosynthesis during biomass growth and released again during utilization. Due to its low energy density, direct use of biomass is not convenient. Thus, it is necessary to convert biomass to fuel gas, such as hydrogen, which can be used cleanly and highly efficiently in fuel cell. Thermo-chemical gasification is likely to be the most cost-effective conversion process and it is promising technology for renewable hydrogen production by utilizing biomass. Biomass gasification produces a mixture of gases (mainly consisting of H 2, CO, CO 2, CH 4 and higher hydrocarbons), solids (char) and... 

Cutting transport is an important goal in drilling operation especially in horizontal and deviated wells since it can cause problems such as stuck pipe, circulation loss and high torque and drag. To this end, this article focused on the affecting parameters on the cutting transport by computational fluid dynamic (CFD) modeling and real operational data. The effect of drilling fluid and cutting density on the pressure drop, deposit ratio and string stress on the cutting transport has been investigated. A systematic validation study is presented by comparing the simulation results against published experimental database. The results showed that by increasing two times of drilling fluid... 

In the last years, an appreciable effort has been directed toward developing empirical models to link the relative permeability of gas condensate reservoirs to the interfacial tension and velocity as well as saturation. However, these models suffer from non-universality and uncertainties in setting the tuning parameters. In order to alleviate the aforesaid infirmities in this study, comprehensive modeling was carried out by employing numerous smart computer-aided algorithms including Support Vector Regression (SVR), Least Square Support Vector Machine (LSSVM), Extreme Learning Machine (ELM), Multilayer Perceptron (MLP), Group Method of Data Handling (GMDH), and Gene Expression Programming... 

Up until now, different methods, including; flow pressure signal, ultrasonic, gamma-ray and combination of them with the neural network approach have been proposed for multiphase flow measurement. More sophisticated techniques such as ultrasonic waves and electricity, as well as high-cost procedures such as gamma waves gradually, can be replaced by simple methods. In this research, only flow parameters such as temperature, viscosity, pressure signals, standard deviation and coefficients of kurtosis and skewness are used as inputs of an artificial neural network to determine the three phase flow rates. The model is validated by the field data which were obtained from separators of two oil... 

Adaptive Reuse is a relatively new approach that aims to restore the relationship between humans and nature by providing a set of concepts and methods that lead to a sustainable interaction between the two. While the ecological approach is one of the most well-known sustainability sciences, it only considers the physical aspects of the relationship between humans and nature and does not account for its semantic dimensions. This research seeks to answer the question of which approach is most effective in establishing a stable relationship between humans and the environment. To achieve this, this article examines the theoretical foundations of Adaptive Reuse and the pathology of the... 

Steam injection process has been considered for a long time as an effective method to exploit heavy oil resources. Over the last decades, Steam Assisted Gravity Drainage (SAGD) has been proved as one of the best steam injection methods for recovery of unconventional oil resources. Recently, Fast-SAGD, a modification of the SAGD process, makes use of additional single horizontal wells alongside the SAGD well pair to expand the steam chamber laterally. This method uses fewer wells and reduces the operational cost compared to a SAGD operation requiring paired parallel wells one above the other. The efficiency of this new method in naturally fractured reservoir is not well understood.... 

Nowadays, the need for industrial processes with sufficient accuracy, efficiency, and flexibility to compete world markets is inevitable. On the other hand, the advent of control techniques and increased computation power of CPUs allow implementation of complex controllers using optimization techniques to provide higher efficiency and economic productivity. Model predictive control refers to a wide range of optimization-based control methods applying explicit models to predict its prospective use. These methods of control compute control signal by minimizing the cost function so that the process output becomes very close to the optimal path. In this paper, we use a new model predictive... 

High availability of software systems is an essential requirement for pervasive computing environments. In such systems self-adaptation, using dynamic reconfiguration is also a key feature. However, dynamic reconfiguration potentially decreases the system availability by making parts of the system temporary frozen, especially during incomplete or faulty execution of the reconfiguration process. In this paper, we propose Assured Dynamic Reconfiguration Framework (ADRF), consisting of run-time analysis phases, assuring the desired correctness and completeness of dynamic reconfiguration process. We also specify factors that affect availability of reconfigurable software in pervasive computing... 

Background: Osteoporosis is one of the most common bone system diseases that is associated with an increased risk of bone fractures and causes many complications for patients. With age, the prevalence of this disease increases so that it has become a serious problem among the elders. In this study, the prevalence of osteoporosis among elders around the world is examined to gain an understanding of its prevalence pattern. Methods: In this systematic review and meta-analysis, articles that have focused on prevalence of osteoporosis in the world’s elders were searched with these key words, such as Prevalence, Osteoporosis, Elders, Older adult in the Science Direct, Embase, Scopus, PubMed, Web... 

The problem of gyrocompassing using inertial sensors, i.e., gyros and accelerometers, is addressed. North finding, with an order of accuracy of one arc-min, is not only required for the initial alignment of inertial navigation systems, but also has a critical role to play in the guidance and navigation of ships that navigate for long periods of time. In this work, after extracting the error model of an inertial navigation system and augmenting it with the error model of inertial sensors, a processing algorithm based on the Kalman filter is designed and simulated to process the navigation system velocity error, and to estimate and correct tilt and heading errors along with gyro drifts and... 

In this study, different concentrations of ascorbic acid (50, 100 and 200 μg/mL) were added to the liquid phase of a calcium phosphate cement (CPC). The cements were immersed in simulated body fluid (SBF) for different intervals and physical, physicochemical and mechanical properties of them were evaluated. The release of added ascorbic acid from CPCs into the SBF solution was also studied. From the results, both setting time and injectability of CPC decreased by adding ascorbic acid, however the compressive strength was sharply increased before soaking in SBF solution. But, the compressive strength values of all cements (with or without ascorbic acid) soaked in SBF solution for more than 7...